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The other day on a science channel I saw a demonstration of the VISAR<br>
image stabilization and enhancement software/hardware.<br>
<a href="http://science.nasa.gov/headlines/y2000/ast31aug_1.htm">Visar
Story</a><br>
<a href="http://solutions.intergraph.com/hardware/vas/">Video Analyst®
System</a><br>
They used it to look at a licence plate, stabilize a guy's water skiing
video, and<br>
some other stuff. They explained that it takes information from
multiple frames to<br>
form the higher resolution output. The demonstration of the priciple
was with an <br>
overhead projector and multiple blurry transparencies of Albert
Einstein that when<br>
lined up formed a clearer image. <br>
<br>
So I figured this sort of thing was right up POV's alley =) Just map a
few images<br>
and filter a bit and voila! Unfortunately, I found that judging off
hand the placement<br>
in a scene of a flat box to correct for perspective correction
unrewarding, even if the<br>
image_map seems lined up, when it is squared to viewer (bringing image
along) it is <br>
obvious that the image is still distorted.<br>
<br>
What I would like to do is map the image to an object first, and then
stretch it to be<br>
correct. In other word given 4 points representing something
rectangular in RL that<br>
is in a image, to then stretch the image to match some other set of 4
points (hopefuly<br>
correcting for perspective in the process) Is there some way to do
this sort of thing?<br>
Any input would be helpful.<br>
<br>
Tim Attwood<br>
#macro T(I M)cylinder{0,I*x,.2 rotate 15*M*z translate A pigment{rgb
E}finish<br>
{ambient 1}}#end#macro Y(E O)#local A=y-x+O;T(1,0)T(2,18)T(1,12)#local
A=x+y<br>
+O;T(2,17)T(2,19)#local A=.7*x-.5*y+O;T(.6,0)#end#local
D=seed(2);#local W=1;<br>
#while(W<35)Y(rand(D)*z<9*rand(D)-5,9*rand(D)-5,9>)#local
W=W+1;#end Y(1,4*z)<br>
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